DSSI Class of 2020

Meet the Data Science Summer Institute Class of 2020, whose internships were conducted remotely this year. Download their Summer Slam presentations (PDFs) to get an idea of the type of work our interns undertake during their time at LLNL.

Porter Bagley

Porter Bagley

Porter Bagley, an undergraduate at Brigham Young University, enjoys studying deep text modeling.

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Bryce Barclay

A PhD student at Arizona State University, Bryce Barclay worked on acceleration of multi-species transport by dimensionality reduction in combustion engine computational fluid dynamics.

Sabyasachi Basu

Sabyasachi Basu

A PhD student at the University of California, Santa Cruz, Sabyasachi Basu worked on understanding temporal subsampling for flow fields.

Cazamere Comrie

Cazamere Comrie

Interested in wireless networking, Cazamere Comrie is pursuing his M.S. at the University of California, Davis.

Justin Crum

Justin Crum

During his internship, University of Arizona PhD student Justin Crum worked on the Tardigrade project.

Adela DePavia

Adela DePavia

A PhD student at the University of Chicago, Adela DePavia developed new parametric probability distributions over sets and hypergraphs that can reasonably be inferred from data.

Alec Dunton

Alec Dunton

Alec Dunton is a PhD student at the University of Colorado, Boulder. During his internship he studied variational precision algorithms for dimensionality reduction techniques.

Duy Duong-Tran

Duy Duong-Tran

A PhD student at Purdue University, Duy Duong-Tran studies network properties of brain connectivity.

Jose Garcia-Esparza

Jose Garcia-Esparza

Jose Garcia-Esparza is pursuing a B.S. at the University of California, Merced. His internship supported machine learning research for the Feedstock Optimization project, which entailed developing and evaluating ML techniques for the prediction of material properties.

Craig Gross

Craig Gross

A PhD student at Michigan State University, Craig Gross worked on the Arcelor Mittal project. During his internship he learned current processes for running fluid mechanics simulations using OpenFoam software on HPC resources.

Emilia Grzesiak

Emilia Grzesiak

Emilia Grzesiak, a graduate student at Duke University, is interested in the CRISPR Genetic Engineering Detection project.

Anthony Guerra

Anthony Guerra

Anthony Guerra is pursuing an M.S. at the University of Southern California. His internship explored a data science pipeline: taking raw imagery, converting it into a usable format, and using that imagery to train a convolutional neural network for classification and detection.

Shoya Iwanami

Shoya Iwanami

Shoya Iwanami is pursuing a PhD at Kyushu University's (Japan) graduate school of Systems Life Sciences. Shoya's internship project combined machine learning with adaptive sampling molecular dynamics methods to study the reversible binding-unbinding process of a molecular force probe.

Sean Kulinski

Sean Kulinski

Sean Kulinski, a Purdue University PhD student, is interested in safe and trustworthy machine learning.

Joy Mueller

Joy Mueller

Joy Mueller, a PhD student at the University of Colorado, Boulder, supported the Mulitlevel Methods project. This effort involved developing deep neural networks for accelerating Markov Chain Monte Carlo simulations.

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Jordan Murphy

Jordan Murphy is pursuing a PhD in Aerospace Engineering at the University of Colorado, Boulder. Jordan's internship focused on simulation, inference, and prediction for stochastic orbit models.

Michelle Ngo

Michelle Ngo

Michelle Ngo is pursuing a PhD at the University of California, Irvine. During her internship she worked on quantifying uncertainties of microscopic nuclear theories.

Adriana Ortiz-Aquino

Adriana Ortiz-Aquino

Adriana Ortiz-Aquino, a PhD student at Kansas State University, worked on the ADAPD Hard Problem 2 project, which involved exploratory analysis of complex structured data.

Leonardo Pinero-Perez

Leonardo Pinero-Perez

An M.S. student at Carnegie Mellon, Leonardo Pinero-Perez worked on the PySCES project developing tools and modeling capabilities to rapidly assess the potential scope of impacts that a cyber-attack can have on energy infrastructure.

Albert Reed

Albert Reed

Albert Reed, a PhD student at Arizona State University, worked on a computed tomography reconstruction project using generative adversarial networks.

Jack Swett

Jack Swett

A PhD student at the University of California, Davis, Jack Swett worked on the MADSTARE project during his internship.

Ayme Tomson

Ayme Tomson

Ayme Tomson is a PhD student at the University of California, Merced, working on the Valkyrie project, which is focused on information extraction from scientific publications.

Kaushik Velusamy

Kaushik Velusamy

Kaushik Velusamy, a PhD student at the University of Maryland, investigated pattern matching in dynamic graphs during his internship.

Takahiro Yamakoshi

Takahiro Yamakoshi

Takahiro Yamakoshi is pursuing at PhD in Informatics at Nagoya University (Japan). Takahiro's internship included using document relevance as distant supervision for domain-specific information extraction, as well as generating semantic graphs from a set of published articles.

Shehtab Zaman

Shehtab Zaman

Shehtab Zaman is pursuing his M.S. at Binghamton University. During his internship he investigated scalable deep learning and second order methods using the LBANN toolkit on GPU-accelerated HPC systems.

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Zhi Zhang

A PhD student at the University of California, Davis, Zhi Zhang's internship focused on a project with the American Heart Association.

Gaofei Zhang

Gaofei Zhang

Gaofei Zhang is a PhD student at the University of Notre Dame. During her internship, she worked on the DANCE project.

Teagan Zuniga

Teagan Zuniga

An undergraduate at the University of California, Merced, Teagan Zuniga developed an approach for organizing and retrieving nuclear safeguards data in a safeguards knowledge repository.